It is clear that false positives consume a lot of cybersecurity analyst’s work hours. There is a need to avoid them to prevent cybersecurity teams from being overloaded. But before getting into their prevention, let’s have a look at what causes these alerts.
Inflexible configuration: Most of the firewalls and other cybersecurity systems are configured according to standard policies and protocols, and they strictly adhere to these policies. Hence, even the slightest deviation from normal behaviour causes false positives.
Heuristic analysis on bits of information: In the Heuristic analysis, a suspicious code or packet is isolated. The isolated code is then allowed to run through simulated cybersecurity measures and then flagged based on outputs. Even this method can prove to be quite ineffective, leading to a considerable number of false positives.
Both the causes mentioned above and several others can be avoided with the help of contextual intelligence. Using contextual intelligence for security will enable you to define your own policies based on granular contexts. This will help avoid false positives flagged because of slight deviations from standard protocols but appropriate according to your policies.
Also, instead of isolating a bit of suspicious code like in Heuristic analysis, contextual intelligence will analyze the entire data packets or code to flag anything uncommon and raise an alert. This will avoid false positives caused based on bits of information and enhance data security.
A context-based data leak prevention firewall will help you add a contextual intelligence layer to your cybersecurity systems to minimize false positives. This will save time for your security teams that can be used to investigate serious alerts that require immediate attention. Context-based data leak prevention firewall also allows you to create your own standards of data flow regulations to avoid any data exploitation and improve data security.